Saturday, 25th August 2018

Serverless for data scientists (via) Slides and accompanying notes from a talk by Mike Lee Williams at PyBay, providing an overview of Zappa and diving a bit more deeply into pywren, which makes it trivial to parallelize a function across a set of AWS lambda instances (serverless Python map() execution essentially). I really like this format for sharing presentations—I used something similar for my own PyBay talk. # 11:01 pm

Computational and Inferential Thinking: The Foundations of Data Science. Free online textbook written for the UC Berkeley Foundations of Data Science class. The examples are all provided as Jupyter notebooks, using the mybinder web application to allow students to launch interactive notebooks for any of the examples without having to install any software on their own machines. # 10:13 pm

Most administrators will force users to change their password at regular intervals, typically every 30, 60 or 90 days. This imposes burdens on the user (who is likely to choose new passwords that are only minor variations of the old) and carries no real benefits as stolen passwords are generally exploited immediately. [...] Regular password changing harms rather than improves security, so avoid placing this burden on users. However, users must change their passwords on indication or suspicion of compromise.

In case you missed it: @GoogleColab can open any @ProjectJupyter notebook directly from @github!
To run the notebook, just replace “github.com” with “colab.research.google.com/github/” in the notebook URL, and it will be loaded into Colab.

Honeycomb changelog (via) Too few hosted services have detailed user-facing changelogs. This one from Honeycomb (a metrics, tracing and observavility platform) is a particularly great example. I especially like the use of animated screenshots, something I’ve been evangelizing pretty heavily recently for internal communication at work. # 3:12 am

I don’t like Jupyter Notebooks—a presentation by Joel Grus (via) Fascinating talk by Joel Grus at the Jupyter conference in New York. He highlights some of the drawbacks of he Jupyter way of working, including the huge confusion that can come from the ability to execute cells out of order (something Observable notebooks solve brilliantly using spreadsheet-style reactive cell associations). He also makes strong arguments that notebooks encourage a way of working that discourages people from producing stable, repeatable and well tested code. # 3:04 am